Tumor Microenvironment Hijacks and Accelerates a Physiological Myeloid Senescence Signature Associated with Pan-Cancer Immunosuppression and Prognostic Stratification

Immunosenescence is a critical driver of tumor initiation and progression. In this study, we systematically characterized immune cell senescence by integrating transcriptomic profiles from 17 physiologically aged tissues with pan-cancer single-cell datasets, encompassing 206 samples across nine cancer types. Cross-tissue comparison of senescence-associated alterations, integrated with spatial transcriptomics, revealed that malignant cells triggered senescence in the core myeloid subpopulation designated Mac_DAB2 via a conserved MIF-CD74 signaling axis. By integrating shared myeloid differentiation programs across normal tissues and the tumor microenvironment (TME) with their transcriptional regulatory networks, we defined a myeloid senescence-associated gene (MSAG) signature. This signature successfully distinguishes a senescence-associated, immunosuppressive subtype linked to poor prognosis in pan-cancer cohorts. Finally, we established the MSAG.SIG prognostic model using an ensemble framework of 117 machine learning algorithms, which demonstrated robust and consistent predictive performance across multiple independent cohorts. Overall, this study elucidates the mechanisms underlying TME-driven myeloid senescence, establishes MSAG as a conceptual framework for characterizing myeloid immunosenescence, and provides a clinically relevant pan-cancer prognostic tool with translational potential.

Authors

Institutions

Publication Details

Journal
International Journal of Molecular Sciences
Published
2026-06-24
DOI
https://doi.org/10.3390/ijms27135688
Primary Topic
Macrophage Migration Inhibitory Factor
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Tumor Microenvironment Hijacks and Accelerates a Physiological Myeloid Senescence Signature Associated with Pan-Cancer Immunosuppression and Prognostic Stratification

Caiyu Zhang, Shangwei Ning, Qianyi Lu, Tengyue Li et al.
International Journal of Molecular Sciences
Macrophage Migration Inhibitory Factor
article

Tumor Microenvironment Hijacks and Accelerates a Physiological Myeloid Senescence Signature Associated with Pan-Cancer Immunosuppression and Prognostic Stratification

Caiyu Zhang, Shangwei Ning, Qianyi Lu, Tengyue Li, Jie Yang, Jialu Zhang, Jiajun Zhou, Gao Y, Han Jiang, Yakun Zhang
article en

Abstract

Immunosenescence is a critical driver of tumor initiation and progression. In this study, we systematically characterized immune cell senescence by integrating transcriptomic profiles from 17 physiologically aged tissues with pan-cancer single-cell datasets, encompassing 206 samples across nine cancer types. Cross-tissue comparison of senescence-associated alterations, integrated with spatial transcriptomics, revealed that malignant cells triggered senescence in the core myeloid subpopulation designated Mac_DAB2 via a conserved MIF-CD74 signaling axis. By integrating shared myeloid differentiation programs across normal tissues and the tumor microenvironment (TME) with their transcriptional regulatory networks, we defined a myeloid senescence-associated gene (MSAG) signature. This signature successfully distinguishes a senescence-associated, immunosuppressive subtype linked to poor prognosis in pan-cancer cohorts. Finally, we established the MSAG.SIG prognostic model using an ensemble framework of 117 machine learning algorithms, which demonstrated robust and consistent predictive performance across multiple independent cohorts. Overall, this study elucidates the mechanisms underlying TME-driven myeloid senescence, establishes MSAG as a conceptual framework for characterizing myeloid immunosenescence, and provides a clinically relevant pan-cancer prognostic tool with translational potential.

International Journal of Molecular SciencesVol. 27(13)
Harbin Medical University (CN)
Openalex Percentile: Top 10%
Macrophage Migration Inhibitory Factor
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.